Unbiasing Fermionic Quantum Monte Carlo with a Quantum Computer

Understand

Many-electron problems pose some of the greatest challenges in computational science, with important applications across many fields of modern science.

• Fermionic quantum Monte Carlo (QMC) methods are among the most powerful approaches to these problems.
• However, they can be severely biased when controlling the fermionic sign problem using constraints, as is necessary for scalability.
• Here we propose an approach that combines constrained QMC with quantum computing tools to reduce such biases.